Sitemap - 2023 - Machine learning at scale
Changes ahead for Machine Learning at scale!
#36 Transformers as.. Support Vector Machines?!
#34 Scalable Second-order Optimizer for Language Model Pre-training
#33 Why Data Science projects fail?
#32 LoRA: Low rank adaptation. Finetuning LLM faster!
#31 Mixture of Experts for inference speed-ups of large scale Machine Learning models.
#30 Pruning vs Quantization. Final showdown!
#29 Object detection: one stage vs two stage networks and evaluation.
#28 Evaluating Machine Learning ranking models offline and online
#27 Gensyn: Decentralised Compute for Machine Learning. The solutions. [Part 2]
#26 Gensyn: Decentralised Compute for Machine Learning. An introduction. [Part 1]
#25 Genuinely Distributed Byzantine Machine Learning.
#24 Pruning LLMs in OneShot with SparseGPT.
#23 Compressing LLMs using novel quantization techniques.
#22 Machine Learning Distributed Training.
#20 Machine Learning Features store challenges from Constructor.io
#17 Uber's Offline Platform For Optimal Feature Discovery.
#16 Robust machine learning models in an adversarial world.
#15 Near real-time personalization at LinkedIn.
#14 Machine learning models: explainability and interpretability.
#13 How Netflix built a media understanding platform for ML innovations.
#11 How Pinterest fights harmful content with Machine Learning.
#10 150 Successful Machine Learning Models: Lessons Learned at Booking.com
#9 Reddit's ML Model Deployment and Serving Architecture
#8 Meta's AI platform for engineers across the company
#7 How DoorDash maintains models accuracy through a monitoring system.
#6 How LinkedIn built a Machine Learning system focused on Explainable AI?
# 5 How Uber continuously deploys Machine learning models at scale?
#4 How Yelp predicts Wait Time for your favourite restaurant?
#3 Technical debt in Machine learning systems has very high interest rate.
#2 How TikTok Real Time Recommendation algorithm scales to billions?